A robust comparison of dynamical scenarios in a glass-forming liquid

We use Bayesian inference methods to provide fresh insights into the sub-nanosecond dynamics of glycerol, a prototypical glass-forming liquid. To this end, quasielastic neutron scattering data as a function of temperature have been analyzed using a minimal set of underlying physical assumptions. On the basis of this analysis, we establish the unambiguous presence of three distinct dynamical processes in glycerol, namely, translational diffusion of the molecular centre of mass and two additional localized and temperature-independent modes. The neutron data also provide access to the characteristic length scales associated with these motions in a model-independent manner, from which we conclude that the faster (slower) localized motions probe longer (shorter) length scales. Careful Bayesian analysis of the entire scattering law favors a heterogeneous scenario for the microscopic dynamics of glycerol, where molecules undergo either the faster and longer or the slower and shorter localized motions.Peer ReviewedPostprint (author's final draft

Radial Basis Function for Breast Lesion Detection from MammoWave Clinical Data

Recently, a novel microwave apparatus for breast lesion detection (MammoWave), uniquely able to function in air with 2 antennas rotating in the azimuth plane and operating within the band 1-9 GHz has been developed. Machine learning (ML) has been implemented to understand information from the frequency spectrum collected through MammoWave in response to the stimulus, segregating breasts with and without lesions. The study comprises 61 breasts (from 35 patients), each one with the correspondent output of the radiologist's conclusion (i.e., gold standard) obtained from echography and/or mammography and/or MRI, plus pathology or 1-year clinical follow-up when required. The MammoWave examinations are performed, recording the frequency spectrum, where the magnitudes show substantial discrepancy and reveals dissimilar behaviours when reflected from tissues with/without lesions. Principal component analysis is implemented to extract the unique quantitative response from the frequency response for automated breast lesion identification, engaging the support vector machine (SVM) with a radial basis function kernel. In-vivo feasibility validation (now ended) of MammoWave was approved in 2015 by the Ethical Committee of Umbria, Italy (N. 6845/15/AV/DM of 14 October 2015, N. 10352/17/NCAV of 16 March 2017, N 13203/18/NCAV of 17 April 2018). Here, we used a set of 35 patients. According to the radiologists conclusions, 25 breasts without lesions and 36 breasts with lesions underwent a MammoWave examination. The proposed SVM model achieved the accuracy, sensitivity, and specificity of 91%, 84.40%, and 97.20%. The proposed ML augmented MammoWave can identify breast lesions with high accuracy

On the microscopic mechanism behind the purely orientational disorder-disorder transition in the plastic phase of 1-chloroadamantane

Globular molecules of 1-chloroadamantane form a plastic phase in which the molecules rotate in a restrained way, but with their centers of mass forming a crystalline ordered lattice. Plastic phases can be regarded as test cases for the study of disordered phases since, contrary to what happens in the liquid phase, there is a lack of stochastic translational degrees of freedom. When the temperature is increased, a hump in the specific heat curve is observed indicating a change in the energetic footprint of the dynamics of the molecules. This change takes place without a change in the symmetry of the crystalline lattice, i.e. no first-order transition is observed between temperatures below and above the calorimetric hump. This implies that subtle changes in the dynamics of the disordered plastic phase concerning purely orientational degrees of freedom should appear at the thermodynamic anomaly. Accordingly, we describe, for the first time, the microscopic mechanisms behind a disorder–disorder transition through the analysis of neutron diffraction and QENS experiments. The results evince a change in the molecular rotational dynamics accompanied by a continuous change in density.Peer ReviewedPreprin

Breast lesion detection through MammoWave device: microwave images’ parameters

MammoWave is a microwave imaging device for breast lesions detection, which operates using two (azimuthally rotating) antennas without any matching liquid. Images, subsequently obtained by resorting to Huygens Principle, are intensity maps, representing the homogeneity of tissues’ dielectric properties. In the paper: “Breast lesion detection through MammoWave device: empirical detection capability assessment of microwave images’ parameters”, we propose to generate, for each breast, a set of conductivity weighted microwave images by using different values of conductivity in the Huygens Principle imaging algorithm. Next, microwave images’ parameters, i.e. features, are introduced to quantify the non-homogenous behaviour of the image. This data set contains such features. We empirically verify on 103 breasts that a selection of these features may allow distinction between breasts with no radiological finding (NF ) and breasts with radiological findings (WF), i.e. with lesions which may be benign or malign. Statistical significance was set at p <0.05. We obtained single features Area Under the receiver operating characteristic Curves (AUCs) spanning from 0.65 to 0.69. In addition, an empirical rule-of-thumb allowing breast assessment is introduced using a binary score S operating on an appropriate combination of features. Performances of such rule-of-thumb are evaluated empirically, obtaining a sensitivity of 74%, which increases to 84% when considering dense breasts only

Amusement ride controls and operating procedures A literature review

SIGLEAvailable from British Library Document Supply Centre-DSC:4274.854(98/24) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Electromagnetically characterized gelatinous-based phantoms for breast microwave imaging

The present work proposes a procedure based on a modified recipe to fabricate electromagnetically characterized phantoms, made of gelatinous-based mixture. As a main advantage we highlight the use of commercially available and very inexpensive gelatin along with the addition of food colorants for the phantom assembly. Furthermore, we have demonstrated that by storing the samples in a refrigerator at a stable temperature of 4°C, the phantoms maintain stable dielectric properties up to 14 days. Their dielectric properties have been measured in the [1-8.5] GHz frequency range using a coaxial probe kit. The promising results demonstrate the potential of the recipe method to realize multistrate breast phantoms representing different tissues

A robust comparison of dynamical scenarios in a glass-forming liquid

We use Bayesian inference methods to provide fresh insights into the sub-nanosecond dynamics of glycerol, a prototypical glass-forming liquid. To this end, quasielastic neutron scattering data as a function of temperature have been analyzed using a minimal set of underlying physical assumptions. On the basis of this analysis, we establish the unambiguous presence of three distinct dynamical processes in glycerol, namely, translational diffusion of the molecular centre of mass and two additional localized and temperature-independent modes. The neutron data also provide access to the characteristic length scales associated with these motions in a model-independent manner, from which we conclude that the faster (slower) localized motions probe longer (shorter) length scales. Careful Bayesian analysis of the entire scattering law favors a heterogeneous scenario for the microscopic dynamics of glycerol, where molecules undergo either the faster and longer or the slower and shorter localized motions.Peer Reviewe

Radial Basis Function for Breast Lesion Detection from MammoWave Clinical Data

Recently, a novel microwave apparatus for breast lesion detection (MammoWave), uniquely able to function in air with 2 antennas rotating in the azimuth plane and operating within the band 1–9 GHz has been developed. Machine learning (ML) has been implemented to understand information from the frequency spectrum collected through MammoWave in response to the stimulus, segregating breasts with and without lesions. The study comprises 61 breasts (from 35 patients), each one with the correspondent output of the radiologist’s conclusion (i.e., gold standard) obtained from echography and/or mammography and/or MRI, plus pathology or 1-year clinical follow-up when required. The MammoWave examinations are performed, recording the frequency spectrum, where the magnitudes show substantial discrepancy and reveals dissimilar behaviours when reflected from tissues with/without lesions. Principal component analysis is implemented to extract the unique quantitative response from the frequency response for automated breast lesion identification, engaging the support vector machine (SVM) with a radial basis function kernel. In-vivo feasibility validation (now ended) of MammoWave was approved in 2015 by the Ethical Committee of Umbria, Italy (N. 6845/15/AV/DM of 14 October 2015, N. 10352/17/NCAV of 16 March 2017, N 13203/18/NCAV of 17 April 2018). Here, we used a set of 35 patients. According to the radiologists conclusions, 25 breasts without lesions and 36 breasts with lesions underwent a MammoWave examination. The proposed SVM model achieved the accuracy, sensitivity, and specificity of 91%, 84.40%, and 97.20%. The proposed ML augmented MammoWave can identify breast lesions with high accuracy

Microscopic dynamics of glycerol: a QENS study

We report on a quasielastic incoherent neutron scattering (QENS) experiment on liquid glycerol. QENS data were collected at the temperature T=380 K and with a resolution (FWHM) R=55μeV. The analysis of the quasielastic signal enables us to draw a consistent picture of the diffusive mechanism on a picosecond time scale and to compare with most recent models for glycerol dynamics. Model selection, performed with the fitting algorithm FABADA, gives us a preliminary description about the motions of the glycerol molecules in its liquid state

Microscopic dynamics of glycerol: a QENS study

We report on a quasielastic incoherent neutron scattering (QENS) experiment onliquid glycerol. QENS data were collected at thetemperature T=380 K and witharesolution(FWHM)R=55µeV.The analysis of the quasielastic signal enables us to draw a consistentpicture of the diffusive mechanism on a picosecond time scale and to compare with most recentmodels for glycerol dynamics. Model selection, performed with the fitting algorithm FABADA, givesus a preliminary description about the motions of the glycerol molecules in its liquid stat